Point, polygon, or marker? In search of the best geographic entity for mapping cultural ecosystem services using the online public participation geographic information systems tool, “My Green Place”

ABSTRACT

The mapping of cultural ecosystem services through online public participation GIS (PPGIS) has predominantly relied on geographic entities, such as points and polygons, to collect spatial data, regardless of their limitations. As the potential of online PPGIS to support planning and design keeps growing, so does the need for more knowledge about data quality and suitable geographic entities to collect data. Using the online PPGIS tool, “My Green Place,” 449 respondents mapped cultural ecosystem services in Ghent by using all three geographic entities: point, polygon, and the novel “marker.” The three geographic entities’ accuracy was analyzed through a quadrat analysis, regressions against the collective truth, the Akaike information criterion, and a preference test based on the survey’s outcomes. The results show that the point reflects the weakest the collective truth, especially for mapping dynamic cultural practices, and the marker reflects it the strongest. The polygon’s performance compares to that of the marker’s, albeit slightly weaker. The marker delivers a more nuanced image of the respondents’ input, is simpler to use, and has less risk of spatial errors. Therefore, we suggest using the marker instead of the point and the polygon when collecting spatial data in future cultural ecosystem services research.

KEYWORDS:

• Public participation GIS (PPGIS)
• cultural ecosystem services (CES)
• green open spaces
• geographic entity (GE)

Acknowledgments

We, the authors, would like to thank Mr. Bart de Wit for his invaluable help in coding the tool that was the centerpiece of this study.

Data and codes availability statement

The data that supports the findings of this study is openly available in Zenodo at the following link: 10.5281/zenodo.4347404

Disclosure statement

No potential conflict of interest was reported by the author(s).

Supplemental data

Supplemental data for this article can be accessed here.

Correction Statement

This article has been republished with minor changes. These changes do not impact the academic content of the article.

Notes

1. In the social sciences, triangulation refers to the application and combination of several research methods in the study of the same phenomenon; do not confuse it with GIS triangulation.

2. Note that in this regression, the original scores rather than the rescaled ones were applied. This did not affect the results for the R-square and AIC.

Additional information

Funding

This study is part of a project that has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 765389, RECOMS.